==================================================Ascend ============================= test session starts ============================== platform linux -- Python 3.9.19, pytest-6.2.5, py-1.11.0, pluggy-1.5.0 rootdir: /home/jenkins/mindspore/testcases/testcases/tests/st/mint, configfile: ../../../../../../sault/virtual_test/virtualenv_004/sault/config/pytest.ini plugins: mock-3.14.0, hydra-core-1.3.2, forked-1.6.0, anyio-4.9.0, xdist-1.32.0 collected 2 items test_permute.py . [hook] pytest_runtest_teardown:test_permute_zero_bias[pynative] tests/st/mint/test_permute.py::test_permute_zero_bias[pynative],max_mem:2.0M TotalTime = 5.71339, [33] [bootstrap]: 0.00084285 [type_inference]: 1.16647 [event_method]: 1.672e-05 [auto_monad]: 0.00018313 [graph_reusing]: 6.16998e-06 [pre_auto_parallel]: 1.358e-05 [py_interpret_to_execute]: 0.00035053 [rewriter_before_opt_a]: 8.255e-05 [expand_dump_flag]: 3.9e-06 [jit_opt_a]: 0.225032, [2] [Cycle 1]: 0.204793, [27] [switch_simplify]: 9.178e-05 [loop_unroll]: 2.823e-05 [a_1]: 0.200391 [with_stream_mark]: 3.478e-05 [recompute_prepare]: 1.893e-05 [updatestate_depend_eliminate]: 7.89997e-06 [updatestate_assign_eliminate]: 5.71998e-06 [updatestate_loads_eliminate]: 5.33002e-06 [parameter_eliminate]: 2.52001e-06 [specialize_transform]: 1.187e-05 [updatestate_useless_node_eliminater]: 1.565e-05 [accelerated_algorithm]: 1.179e-05 [meta_shard_fg_expand]: 5.17e-06 [get_grad_eliminate_]: 5.774e-05 [merge_forward]: 6.59001e-06 [cell_reuse_recompute_pass]: 1.94e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.201e-05 [j_node_and_user_rematch]: 1.823e-05 [meta_fg_expand]: 4.68001e-06 [replace_old_param]: 1.719e-05 [inline_without_move]: 1.079e-05 [renormalize]: 0.00355919 [add_forward_monad_depend]: 1.557e-05 [auto_monad_grad]: 2.92002e-06 [auto_monad_eliminator]: 2.772e-05 [cse]: 5.25e-05 [replace_applicator]: 3.104e-05 [Cycle 2]: 0.00062994, [27] [switch_simplify]: 1.126e-05 [loop_unroll]: 9.39998e-06 [a_1]: 0.00025286 [with_stream_mark]: 2.035e-05 [recompute_prepare]: 1.096e-05 [updatestate_depend_eliminate]: 6.72002e-06 [updatestate_assign_eliminate]: 6.30002e-06 [updatestate_loads_eliminate]: 4.48999e-06 [parameter_eliminate]: 1.89e-06 [specialize_transform]: 9.66e-06 [updatestate_useless_node_eliminater]: 1.218e-05 [accelerated_algorithm]: 1.068e-05 [meta_shard_fg_expand]: 3.61001e-06 [get_grad_eliminate_]: 9.82001e-06 [merge_forward]: 5.81e-06 [cell_reuse_recompute_pass]: 2.99001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.329e-05 [j_node_and_user_rematch]: 1.52e-05 [meta_fg_expand]: 3.69002e-06 [replace_old_param]: 1.42e-05 [inline_without_move]: 9.76e-06 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.91998e-06 [auto_monad_grad]: 2.17999e-06 [auto_monad_eliminator]: 1.13e-05 [cse]: 2.17e-05 [replace_applicator]: 1.01e-05 [py_interpret_to_execute_after_opt_a]: 1.975e-05 [rewriter_after_opt_a]: 0.00055363 [convert_after_rewriter]: 1.721e-05 [order_py_execute_after_rewriter]: 7.36999e-06 [mutable_eliminate]: 0.000849 [jit_opt_b]: 9.753e-05, [1] [Cycle 1]: 8.663e-05, [2] [frontend_op_eliminate]: 3.839e-05 [inline_after_opt_a]: 3.305e-05 [cconv]: 3.872e-05 [loop_unroll]: 0.00049398 [jit_opt_after_cconv]: 0.00026122, [1] [Cycle 1]: 0.00025322, [11] [c_1]: 5.774e-05 [parameter_eliminate]: 5.41998e-06 [updatestate_depend_eliminate]: 1.212e-05 [updatestate_assign_eliminate]: 5.08002e-06 [updatestate_loads_eliminate]: 4.87e-06 [cse]: 3.913e-05 [call_graph_tuple_transform]: 4.302e-05 [tuple_list_get_item_eliminator]: 1.123e-05 [none_parameter_eliminate]: 1.96003e-06 [renormalize]: 7.30011e-07 [switch_simplify]: 1.048e-05 [remove_dup_value]: 2.168e-05 [partial_unused_args_eliminate]: 2.31998e-06 [environ_conv]: 2.737e-05 [add_recomputation]: 9.772e-05 [cse_after_recomputation]: 3.72e-05, [1] [Cycle 1]: 2.848e-05, [1] [cse]: 2.023e-05 [auto_monad_reorder]: 3.688e-05 [get_jit_bprop_graph]: 3.02002e-06 [rewriter_after_jit_bprop_graph]: 0.00014917 [opt_after_jit_grad]: 0.00058626 [symbol_engine_optimizer]: 0.00011461, [1] [Cycle 1]: 0.00010575, [6] [build]: 7.61001e-06 [elim_shapecalc]: 1.533e-05 [elim_not_effective]: 2.316e-05 [opt_reshape]: 1.051e-05 [fold_const_symbol]: 1.521e-05 [renormalize]: 5.3001e-07 [validate]: 8.768e-05 [backend_pass]: 1.02998e-06 [task_emit]: 4.31645 [execute]: 1.139e-05 Sums bootstrap : 0.000843s : 0.01% type_inference : 1.166467s : 20.49% event_method : 0.000017s : 0.00% auto_monad : 0.000183s : 0.00% graph_reusing : 0.000006s : 0.00% pre_auto_parallel : 0.000014s : 0.00% py_interpret_to_execute : 0.000351s : 0.01% rewriter_before_opt_a : 0.000083s : 0.00% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000103s : 0.00% jit_opt_a.loop_unroll : 0.000038s : 0.00% jit_opt_a.a_1 : 0.200644s : 3.52% jit_opt_a.with_stream_mark : 0.000055s : 0.00% jit_opt_a.recompute_prepare : 0.000030s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000015s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000012s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000010s : 0.00% jit_opt_a.parameter_eliminate : 0.000004s : 0.00% jit_opt_a.specialize_transform : 0.000022s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000028s : 0.00% jit_opt_a.accelerated_algorithm : 0.000022s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000009s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000068s : 0.00% jit_opt_a.merge_forward : 0.000012s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000005s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000055s : 0.00% jit_opt_a.j_node_and_user_rematch : 0.000033s : 0.00% jit_opt_a.meta_fg_expand : 0.000008s : 0.00% jit_opt_a.replace_old_param : 0.000031s : 0.00% jit_opt_a.inline_without_move : 0.000021s : 0.00% jit_opt_a.renormalize : 0.003559s : 0.06% jit_opt_a.add_forward_monad_depend : 0.000017s : 0.00% jit_opt_a.auto_monad_grad : 0.000005s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000039s : 0.00% jit_opt_a.cse : 0.000074s : 0.00% jit_opt_a.replace_applicator : 0.000041s : 0.00% py_interpret_to_execute_after_opt_a : 0.000020s : 0.00% rewriter_after_opt_a : 0.000554s : 0.01% convert_after_rewriter : 0.000017s : 0.00% order_py_execute_after_rewriter : 0.000007s : 0.00% mutable_eliminate : 0.000849s : 0.01% jit_opt_b.frontend_op_eliminate : 0.000038s : 0.00% jit_opt_b.inline_after_opt_a : 0.000033s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000494s : 0.01% jit_opt_after_cconv.c_1 : 0.000058s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000012s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.cse : 0.000039s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000043s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000011s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000001s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000010s : 0.00% remove_dup_value : 0.000022s : 0.00% partial_unused_args_eliminate : 0.000002s : 0.00% environ_conv : 0.000027s : 0.00% add_recomputation : 0.000098s : 0.00% cse_after_recomputation.cse : 0.000020s : 0.00% auto_monad_reorder : 0.000037s : 0.00% get_jit_bprop_graph : 0.000003s : 0.00% rewriter_after_jit_bprop_graph : 0.000149s : 0.00% opt_after_jit_grad : 0.000586s : 0.01% symbol_engine_optimizer.build : 0.000008s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000015s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000023s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000011s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000015s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000088s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 4.316454s : 75.82% execute : 0.000011s : 0.00% Time group info: ------[substitution.] 0.001276 45 1.07% : 0.000014s : 2: substitution.depend_value_elim 0.25% : 0.000003s : 4: substitution.elim_not_effective 0.16% : 0.000002s : 4: substitution.fold_const_symbol 1.69% : 0.000022s : 6: substitution.graph_param_transform 93.22% : 0.001189s : 3: substitution.inline 0.54% : 0.000007s : 8: substitution.j_node_and_user_rematch 0.63% : 0.000008s : 8: substitution.remove_not_recompute_node 0.60% : 0.000008s : 2: substitution.replace_old_param 1.00% : 0.000013s : 3: substitution.updatestate_pure_node_eliminater 0.83% : 0.000011s : 5: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.166360 2 99.83% : 1.164378s : 1: type_inference.infer 0.17% : 0.001982s : 1: type_inference.specialize ------[replace.] 0.000074 3 100.00% : 0.000074s : 3: replace.inline ------[match.] 0.001183 3 100.00% : 0.001183s : 3: match.inline ------[predicate.] 0.000240 970 1.42% : 0.000003s : 14: predicate.accumulaten_eliminater 1.04% : 0.000002s : 6: predicate.ad_related_special_op_eliminate 0.87% : 0.000002s : 14: predicate.addn_check_dump 1.50% : 0.000004s : 14: predicate.addn_zero_filter 2.72% : 0.000007s : 14: predicate.arithmetic_simplify 1.91% : 0.000005s : 14: predicate.cast_eliminate 0.50% : 0.000001s : 6: predicate.check_bprop_eliminate 0.91% : 0.000002s : 14: predicate.compare_switch_simplify 1.57% : 0.000004s : 14: predicate.depend_value_elim 1.02% : 0.000002s : 14: predicate.dict_get_item_const_eliminator 1.41% : 0.000003s : 14: predicate.dict_get_item_eliminator 1.28% : 0.000003s : 14: predicate.dict_set_item_eliminator 0.95% : 0.000002s : 6: predicate.dumpgradient_eliminate 0.28% : 0.000001s : 6: predicate.elim_not_effective 0.59% : 0.000001s : 6: predicate.elim_shapecalc_of_broadcastargs 1.15% : 0.000003s : 14: predicate.environ_add_const_eliminate 0.95% : 0.000002s : 14: predicate.environ_get_add_eliminate 1.33% : 0.000003s : 14: predicate.environ_get_depend_swap 1.22% : 0.000003s : 14: predicate.environ_get_eliminate 1.00% : 0.000002s : 14: predicate.environ_get_set_eliminate 0.22% : 0.000001s : 6: predicate.fold_const_symbol 1.42% : 0.000003s : 12: predicate.get_grad_eliminate 0.42% : 0.000001s : 6: predicate.graph_param_transform 5.62% : 0.000013s : 29: predicate.inline 1.02% : 0.000002s : 12: predicate.inline_without_move 0.40% : 0.000001s : 12: predicate.j_node_and_user_rematch 1.58% : 0.000004s : 12: predicate.less_batch_normalization 1.11% : 0.000003s : 14: predicate.list_to_tuple_eliminator_ 1.82% : 0.000004s : 20: predicate.load_eliminater 1.11% : 0.000003s : 6: predicate.loop_unroll_after_grad 2.10% : 0.000005s : 30: predicate.loop_unroll_before_grad 1.82% : 0.000004s : 20: predicate.make_slice_get_slice_eliminator 1.50% : 0.000004s : 14: predicate.merge_addn 0.91% : 0.000002s : 14: predicate.minmaximum_grad 1.55% : 0.000004s : 6: predicate.mutable_eliminate 0.47% : 0.000001s : 6: predicate.opt_reshape 1.72% : 0.000004s : 20: predicate.partial_eliminate 1.34% : 0.000003s : 14: predicate.print_const_string_wrapper 1.98% : 0.000005s : 14: predicate.reduce_eliminate 1.51% : 0.000004s : 14: predicate.redundant_stop_gradient_eliminater 0.64% : 0.000002s : 12: predicate.remove_not_recompute_node 1.43% : 0.000003s : 26: predicate.replace_applicator 0.61% : 0.000001s : 12: predicate.replace_old_param 0.37% : 0.000001s : 6: predicate.reset_defer_inline 1.35% : 0.000003s : 14: predicate.reshape_eliminate 1.11% : 0.000003s : 14: predicate.row_tensor_add_zeros_like 0.99% : 0.000002s : 6: predicate.row_tensor_eliminate 1.15% : 0.000003s : 14: predicate.same_eliminate 0.52% : 0.000001s : 12: predicate.set_cell_output_no_recompute 0.99% : 0.000002s : 12: predicate.special_op_eliminate 0.97% : 0.000002s : 12: predicate.specialize_transform 1.70% : 0.000004s : 14: predicate.split_environ_get_set_with_tuple_value 1.28% : 0.000003s : 14: predicate.stack_unstack_eliminate 0.53% : 0.000001s : 6: predicate.switch_call_monad_eliminater 2.35% : 0.000006s : 17: predicate.switch_defer_inline 2.10% : 0.000005s : 17: predicate.switch_layer_defer_inline 8.62% : 0.000021s : 53: predicate.switch_simplify 1.24% : 0.000003s : 14: predicate.tile_eliminate 1.60% : 0.000004s : 14: predicate.transpose_eliminate 1.75% : 0.000004s : 14: predicate.tuple_list_convert_item_index_to_positive 1.62% : 0.000004s : 14: predicate.tuple_list_get_item_depend_reorder 3.76% : 0.000009s : 26: predicate.tuple_list_get_item_eliminator 1.80% : 0.000004s : 14: predicate.tuple_list_set_item_eliminator 1.08% : 0.000003s : 14: predicate.tuple_to_list_eliminator_ 1.52% : 0.000004s : 20: predicate.updatestate_pure_node_eliminater 3.21% : 0.000008s : 32: predicate.updatestate_useless_node_eliminater 1.41% : 0.000003s : 14: predicate.value_based_eliminate 0.39% : 0.000001s : 6: predicate.virtual_view_grad_eliminate 0.64% : 0.000002s : 6: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.003164 23 77.25% : 0.002444s : 18: func_graph_cloner_run.FuncGraphClonerGraph 22.75% : 0.000720s : 5: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 5.918156 76 0.00% : 0.000101s : 1: add_recomputation 0.00% : 0.000189s : 1: auto_monad 0.00% : 0.000040s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.01% : 0.000881s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000021s : 1: convert_after_rewriter 0.00% : 0.000040s : 1: cse_after_recomputation 0.00% : 0.000030s : 1: environ_conv 0.00% : 0.000022s : 1: event_method 0.00% : 0.000018s : 1: execute 0.00% : 0.000006s : 1: expand_dump_flag 0.00% : 0.000006s : 1: get_jit_bprop_graph 0.00% : 0.000009s : 1: graph_reusing 3.80% : 0.225036s : 1: jit_opt_a 0.00% : 0.000265s : 1: jit_opt_after_cconv 0.00% : 0.000101s : 1: jit_opt_b 0.01% : 0.000504s : 1: loop_unroll 0.01% : 0.000860s : 1: mutable_eliminate 3.40% : 0.201063s : 26: opt.transform.jit_opt_a 0.00% : 0.000118s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000060s : 4: opt.transform.jit_opt_b 0.00% : 0.000019s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000025s : 1: opt.transform.mutable_eliminate 0.00% : 0.000040s : 1: opt.transform.opt_after_jit_grad 0.00% : 0.000059s : 4: opt.transform.symbol_engine_opt 0.01% : 0.000613s : 1: opt_after_jit_grad 0.00% : 0.000010s : 1: order_py_execute_after_rewriter 0.00% : 0.000004s : 1: partial_unused_args_eliminate 0.00% : 0.000016s : 1: pre_auto_parallel 0.01% : 0.000357s : 1: py_interpret_to_execute 0.00% : 0.000022s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000025s : 1: remove_dup_value 0.04% : 0.002624s : 1: renormalize.infer 0.02% : 0.000922s : 1: renormalize.specialize 0.00% : 0.000153s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000560s : 1: rewriter_after_opt_a 0.00% : 0.000088s : 1: rewriter_before_opt_a 0.00% : 0.000118s : 1: symbol_engine_optimizer 72.94% : 4.316483s : 1: task_emit 19.71% : 1.166487s : 1: type_inference 0.00% : 0.000116s : 1: validate TotalTime = 2.60606, [33] [bootstrap]: 0.00057569 [type_inference]: 1.45743 [event_method]: 0.0328108 [auto_monad]: 0.00038602 [graph_reusing]: 1.148e-05 [pre_auto_parallel]: 3.85e-06 [py_interpret_to_execute]: 5.702e-05 [rewriter_before_opt_a]: 0.00019152 [expand_dump_flag]: 4.19002e-06 [jit_opt_a]: 0.873568, [4] [Cycle 1]: 0.822218, [27] [switch_simplify]: 0.0002617 [loop_unroll]: 7.706e-05 [a_1]: 0.00173749 [with_stream_mark]: 4.308e-05 [recompute_prepare]: 3.766e-05 [updatestate_depend_eliminate]: 1.457e-05 [updatestate_assign_eliminate]: 1.172e-05 [updatestate_loads_eliminate]: 1.045e-05 [parameter_eliminate]: 4.22998e-06 [specialize_transform]: 2.755e-05 [updatestate_useless_node_eliminater]: 2.814e-05 [accelerated_algorithm]: 2.269e-05 [meta_shard_fg_expand]: 7.05e-06 [get_grad_eliminate_]: 2.243e-05 [merge_forward]: 1.342e-05 [cell_reuse_recompute_pass]: 1.78002e-06 [cell_reuse_handle_not_recompute_node_pass]: 4.699e-05 [j_node_and_user_rematch]: 3.938e-05 [meta_fg_expand]: 0.489829 [replace_old_param]: 0.00014617 [inline_without_move]: 0.00014074 [renormalize]: 0.328533 [add_forward_monad_depend]: 3.305e-05 [auto_monad_grad]: 1.355e-05 [auto_monad_eliminator]: 0.00013533 [cse]: 0.00029384 [replace_applicator]: 0.00028797 [Cycle 2]: 0.0437396, [27] [switch_simplify]: 0.00010224 [loop_unroll]: 9.341e-05 [a_1]: 0.0404345 [with_stream_mark]: 4.561e-05 [recompute_prepare]: 3.799e-05 [updatestate_depend_eliminate]: 1.531e-05 [updatestate_assign_eliminate]: 1.413e-05 [updatestate_loads_eliminate]: 1.363e-05 [parameter_eliminate]: 4.60001e-06 [specialize_transform]: 2.234e-05 [updatestate_useless_node_eliminater]: 9.338e-05 [accelerated_algorithm]: 1.575e-05 [meta_shard_fg_expand]: 7.37002e-06 [get_grad_eliminate_]: 1.459e-05 [merge_forward]: 8.32e-06 [cell_reuse_recompute_pass]: 1.42e-06 [cell_reuse_handle_not_recompute_node_pass]: 3.563e-05 [j_node_and_user_rematch]: 2.638e-05 [meta_fg_expand]: 0.00016686 [replace_old_param]: 2.534e-05 [inline_without_move]: 1.494e-05 [renormalize]: 0.00208404 [add_forward_monad_depend]: 1.04e-05 [auto_monad_grad]: 2.49999e-06 [auto_monad_eliminator]: 3.479e-05 [cse]: 0.00012003 [replace_applicator]: 3.491e-05 [Cycle 3]: 0.00175279, [27] [switch_simplify]: 1.591e-05 [loop_unroll]: 1.387e-05 [a_1]: 0.00037946 [with_stream_mark]: 2.317e-05 [recompute_prepare]: 1.651e-05 [updatestate_depend_eliminate]: 5.266e-05 [updatestate_assign_eliminate]: 6.68e-06 [updatestate_loads_eliminate]: 6.07999e-06 [parameter_eliminate]: 1.74998e-06 [specialize_transform]: 1.398e-05 [updatestate_useless_node_eliminater]: 1.607e-05 [accelerated_algorithm]: 1.268e-05 [meta_shard_fg_expand]: 3.04001e-06 [get_grad_eliminate_]: 1.179e-05 [merge_forward]: 6.81999e-06 [cell_reuse_recompute_pass]: 3.46001e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.713e-05 [j_node_and_user_rematch]: 1.903e-05 [meta_fg_expand]: 4.60999e-06 [replace_old_param]: 1.653e-05 [inline_without_move]: 1.216e-05 [renormalize]: 0.000806 [add_forward_monad_depend]: 7.01999e-06 [auto_monad_grad]: 2.68e-06 [auto_monad_eliminator]: 2.84e-05 [cse]: 4.347e-05 [replace_applicator]: 2.535e-05 [Cycle 4]: 0.00071833, [27] [switch_simplify]: 1.296e-05 [loop_unroll]: 1.172e-05 [a_1]: 0.00029548 [with_stream_mark]: 1.61e-05 [recompute_prepare]: 1.193e-05 [updatestate_depend_eliminate]: 6.89999e-06 [updatestate_assign_eliminate]: 5.25001e-06 [updatestate_loads_eliminate]: 5.79e-06 [parameter_eliminate]: 2.14e-06 [specialize_transform]: 1.227e-05 [updatestate_useless_node_eliminater]: 1.567e-05 [accelerated_algorithm]: 1.261e-05 [meta_shard_fg_expand]: 3.24001e-06 [get_grad_eliminate_]: 1.212e-05 [merge_forward]: 6.34001e-06 [cell_reuse_recompute_pass]: 2.69999e-06 [cell_reuse_handle_not_recompute_node_pass]: 2.495e-05 [j_node_and_user_rematch]: 1.936e-05 [meta_fg_expand]: 3.88999e-06 [replace_old_param]: 1.575e-05 [inline_without_move]: 1.179e-05 [renormalize]: 6.99947e-08 [add_forward_monad_depend]: 1.99e-06 [auto_monad_grad]: 1.91e-06 [auto_monad_eliminator]: 1.851e-05 [cse]: 2.889e-05 [replace_applicator]: 1.421e-05 [py_interpret_to_execute_after_opt_a]: 2.134e-05 [rewriter_after_opt_a]: 0.00023077 [convert_after_rewriter]: 1.531e-05 [order_py_execute_after_rewriter]: 9.21998e-06 [mutable_eliminate]: 0.00099663 [jit_opt_b]: 0.00010167, [1] [Cycle 1]: 9.075e-05, [2] [frontend_op_eliminate]: 3.691e-05 [inline_after_opt_a]: 3.883e-05 [cconv]: 3.851e-05 [loop_unroll]: 0.00054793 [jit_opt_after_cconv]: 0.00029319, [1] [Cycle 1]: 0.00028486, [11] [c_1]: 7.973e-05 [parameter_eliminate]: 5.44e-06 [updatestate_depend_eliminate]: 1.362e-05 [updatestate_assign_eliminate]: 7.3e-06 [updatestate_loads_eliminate]: 5.97001e-06 [cse]: 5.215e-05 [call_graph_tuple_transform]: 3.403e-05 [tuple_list_get_item_eliminator]: 1.213e-05 [none_parameter_eliminate]: 1.66002e-06 [renormalize]: 4.00003e-07 [switch_simplify]: 1.229e-05 [remove_dup_value]: 6.119e-05 [partial_unused_args_eliminate]: 2.69999e-06 [environ_conv]: 1.465e-05 [add_recomputation]: 8.743e-05 [cse_after_recomputation]: 3.615e-05, [1] [Cycle 1]: 2.913e-05, [1] [cse]: 2.151e-05 [auto_monad_reorder]: 3.754e-05 [get_jit_bprop_graph]: 2.41e-06 [rewriter_after_jit_bprop_graph]: 8.38999e-06 [opt_after_jit_grad]: 0.00056023 [symbol_engine_optimizer]: 0.00012201, [1] [Cycle 1]: 0.00011415, [6] [build]: 6.46999e-06 [elim_shapecalc]: 1.694e-05 [elim_not_effective]: 2.463e-05 [opt_reshape]: 1.31e-05 [fold_const_symbol]: 1.911e-05 [renormalize]: 6.40022e-07 [validate]: 7.249e-05 [backend_pass]: 1.30001e-06 [task_emit]: 0.237432 [execute]: 1.031e-05 Sums bootstrap : 0.000576s : 0.02% type_inference : 1.457426s : 56.07% event_method : 0.032811s : 1.26% auto_monad : 0.000386s : 0.01% graph_reusing : 0.000011s : 0.00% pre_auto_parallel : 0.000004s : 0.00% py_interpret_to_execute : 0.000057s : 0.00% rewriter_before_opt_a : 0.000192s : 0.01% expand_dump_flag : 0.000004s : 0.00% jit_opt_a.switch_simplify : 0.000393s : 0.02% jit_opt_a.loop_unroll : 0.000196s : 0.01% jit_opt_a.a_1 : 0.042847s : 1.65% jit_opt_a.with_stream_mark : 0.000128s : 0.00% jit_opt_a.recompute_prepare : 0.000104s : 0.00% jit_opt_a.updatestate_depend_eliminate : 0.000089s : 0.00% jit_opt_a.updatestate_assign_eliminate : 0.000038s : 0.00% jit_opt_a.updatestate_loads_eliminate : 0.000036s : 0.00% jit_opt_a.parameter_eliminate : 0.000013s : 0.00% jit_opt_a.specialize_transform : 0.000076s : 0.00% jit_opt_a.updatestate_useless_node_eliminater : 0.000153s : 0.01% jit_opt_a.accelerated_algorithm : 0.000064s : 0.00% jit_opt_a.meta_shard_fg_expand : 0.000021s : 0.00% jit_opt_a.get_grad_eliminate_ : 0.000061s : 0.00% jit_opt_a.merge_forward : 0.000035s : 0.00% jit_opt_a.cell_reuse_recompute_pass : 0.000009s : 0.00% jit_opt_a.cell_reuse_handle_not_recompute_node_pass : 0.000135s : 0.01% jit_opt_a.j_node_and_user_rematch : 0.000104s : 0.00% jit_opt_a.meta_fg_expand : 0.490004s : 18.85% jit_opt_a.replace_old_param : 0.000204s : 0.01% jit_opt_a.inline_without_move : 0.000180s : 0.01% jit_opt_a.renormalize : 0.331423s : 12.75% jit_opt_a.add_forward_monad_depend : 0.000052s : 0.00% jit_opt_a.auto_monad_grad : 0.000021s : 0.00% jit_opt_a.auto_monad_eliminator : 0.000217s : 0.01% jit_opt_a.cse : 0.000486s : 0.02% jit_opt_a.replace_applicator : 0.000362s : 0.01% py_interpret_to_execute_after_opt_a : 0.000021s : 0.00% rewriter_after_opt_a : 0.000231s : 0.01% convert_after_rewriter : 0.000015s : 0.00% order_py_execute_after_rewriter : 0.000009s : 0.00% mutable_eliminate : 0.000997s : 0.04% jit_opt_b.frontend_op_eliminate : 0.000037s : 0.00% jit_opt_b.inline_after_opt_a : 0.000039s : 0.00% cconv : 0.000039s : 0.00% loop_unroll : 0.000548s : 0.02% jit_opt_after_cconv.c_1 : 0.000080s : 0.00% jit_opt_after_cconv.parameter_eliminate : 0.000005s : 0.00% jit_opt_after_cconv.updatestate_depend_eliminate : 0.000014s : 0.00% jit_opt_after_cconv.updatestate_assign_eliminate : 0.000007s : 0.00% jit_opt_after_cconv.updatestate_loads_eliminate : 0.000006s : 0.00% jit_opt_after_cconv.cse : 0.000052s : 0.00% jit_opt_after_cconv.call_graph_tuple_transform : 0.000034s : 0.00% jit_opt_after_cconv.tuple_list_get_item_eliminator : 0.000012s : 0.00% jit_opt_after_cconv.none_parameter_eliminate : 0.000002s : 0.00% jit_opt_after_cconv.renormalize : 0.000000s : 0.00% jit_opt_after_cconv.switch_simplify : 0.000012s : 0.00% remove_dup_value : 0.000061s : 0.00% partial_unused_args_eliminate : 0.000003s : 0.00% environ_conv : 0.000015s : 0.00% add_recomputation : 0.000087s : 0.00% cse_after_recomputation.cse : 0.000022s : 0.00% auto_monad_reorder : 0.000038s : 0.00% get_jit_bprop_graph : 0.000002s : 0.00% rewriter_after_jit_bprop_graph : 0.000008s : 0.00% opt_after_jit_grad : 0.000560s : 0.02% symbol_engine_optimizer.build : 0.000006s : 0.00% symbol_engine_optimizer.elim_shapecalc : 0.000017s : 0.00% symbol_engine_optimizer.elim_not_effective : 0.000025s : 0.00% symbol_engine_optimizer.opt_reshape : 0.000013s : 0.00% symbol_engine_optimizer.fold_const_symbol : 0.000019s : 0.00% symbol_engine_optimizer.renormalize : 0.000001s : 0.00% validate : 0.000072s : 0.00% backend_pass : 0.000001s : 0.00% task_emit : 0.237432s : 9.13% execute : 0.000010s : 0.00% Time group info: ------[substitution.] 0.003098 271 1.46% : 0.000045s : 12: substitution.depend_value_elim 0.12% : 0.000004s : 5: substitution.elim_not_effective 0.09% : 0.000003s : 5: substitution.fold_const_symbol 29.72% : 0.000921s : 4: substitution.getattr_setattr_resolve 0.34% : 0.000011s : 8: substitution.graph_param_transform 51.06% : 0.001582s : 29: substitution.inline 1.41% : 0.000044s : 4: substitution.inline_without_move 0.64% : 0.000020s : 29: substitution.j_node_and_user_rematch 0.81% : 0.000025s : 13: substitution.minmaximum_grad 0.51% : 0.000016s : 14: substitution.partial_eliminate 0.81% : 0.000025s : 29: substitution.remove_not_recompute_node 2.44% : 0.000076s : 16: substitution.replace_applicator 0.73% : 0.000023s : 17: substitution.replace_old_param 0.25% : 0.000008s : 2: substitution.set_cell_output_no_recompute 0.50% : 0.000015s : 3: substitution.switch_simplify 1.53% : 0.000047s : 13: substitution.tuple_list_convert_item_index_to_positive 1.10% : 0.000034s : 13: substitution.tuple_list_get_item_depend_reorder 3.53% : 0.000109s : 30: substitution.tuple_list_get_item_eliminator 0.87% : 0.000027s : 9: substitution.updatestate_pure_node_eliminater 2.07% : 0.000064s : 16: substitution.updatestate_useless_node_eliminater ------[type_inference.] 1.457302 2 99.77% : 1.453917s : 1: type_inference.infer 0.23% : 0.003385s : 1: type_inference.specialize ------[replace.] 0.000967 54 7.60% : 0.000074s : 3: replace.getattr_setattr_resolve 50.42% : 0.000488s : 29: replace.inline 6.76% : 0.000065s : 1: replace.replace_applicator 9.06% : 0.000088s : 3: replace.switch_simplify 21.24% : 0.000205s : 17: replace.tuple_list_get_item_eliminator 4.91% : 0.000047s : 1: replace.updatestate_useless_node_eliminater ------[match.] 0.002510 54 34.11% : 0.000856s : 3: match.getattr_setattr_resolve 62.16% : 0.001560s : 29: match.inline 0.69% : 0.000017s : 1: match.replace_applicator 0.52% : 0.000013s : 3: match.switch_simplify 1.94% : 0.000049s : 17: match.tuple_list_get_item_eliminator 0.58% : 0.000015s : 1: match.updatestate_useless_node_eliminater ------[predicate.] 0.001085 6056 1.58% : 0.000017s : 101: predicate.accumulaten_eliminater 0.23% : 0.000002s : 8: predicate.ad_related_special_op_eliminate 1.36% : 0.000015s : 101: predicate.addn_check_dump 1.47% : 0.000016s : 101: predicate.addn_zero_filter 1.98% : 0.000022s : 101: predicate.arithmetic_simplify 1.67% : 0.000018s : 101: predicate.cast_eliminate 0.13% : 0.000001s : 8: predicate.check_bprop_eliminate 1.36% : 0.000015s : 101: predicate.compare_switch_simplify 1.42% : 0.000015s : 101: predicate.depend_value_elim 1.36% : 0.000015s : 101: predicate.dict_get_item_const_eliminator 1.48% : 0.000016s : 101: predicate.dict_get_item_eliminator 1.34% : 0.000015s : 101: predicate.dict_set_item_eliminator 0.19% : 0.000002s : 8: predicate.dumpgradient_eliminate 0.10% : 0.000001s : 8: predicate.elim_not_effective 0.18% : 0.000002s : 8: predicate.elim_shapecalc_of_broadcastargs 1.43% : 0.000015s : 101: predicate.environ_add_const_eliminate 1.44% : 0.000016s : 101: predicate.environ_get_add_eliminate 1.40% : 0.000015s : 101: predicate.environ_get_depend_swap 1.31% : 0.000014s : 101: predicate.environ_get_eliminate 1.42% : 0.000015s : 101: predicate.environ_get_set_eliminate 0.07% : 0.000001s : 8: predicate.fold_const_symbol 0.81% : 0.000009s : 44: predicate.get_grad_eliminate 0.65% : 0.000007s : 20: predicate.getattr_setattr_resolve 0.08% : 0.000001s : 8: predicate.graph_param_transform 9.29% : 0.000101s : 163: predicate.inline 1.91% : 0.000021s : 105: predicate.inline_without_move 0.33% : 0.000004s : 44: predicate.j_node_and_user_rematch 0.88% : 0.000010s : 44: predicate.less_batch_normalization 1.68% : 0.000018s : 118: predicate.list_to_tuple_eliminator_ 1.77% : 0.000019s : 126: predicate.load_eliminater 0.29% : 0.000003s : 8: predicate.loop_unroll_after_grad 2.73% : 0.000030s : 187: predicate.loop_unroll_before_grad 1.61% : 0.000017s : 109: predicate.make_slice_get_slice_eliminator 1.30% : 0.000014s : 101: predicate.merge_addn 1.43% : 0.000016s : 101: predicate.minmaximum_grad 0.48% : 0.000005s : 8: predicate.mutable_eliminate 0.16% : 0.000002s : 8: predicate.opt_reshape 2.24% : 0.000024s : 126: predicate.partial_eliminate 2.02% : 0.000022s : 101: predicate.print_const_string_wrapper 1.65% : 0.000018s : 101: predicate.reduce_eliminate 1.89% : 0.000020s : 118: predicate.redundant_stop_gradient_eliminater 0.43% : 0.000005s : 44: predicate.remove_not_recompute_node 2.48% : 0.000027s : 243: predicate.replace_applicator 0.89% : 0.000010s : 105: predicate.replace_old_param 0.11% : 0.000001s : 8: predicate.reset_defer_inline 1.43% : 0.000016s : 101: predicate.reshape_eliminate 1.33% : 0.000014s : 101: predicate.row_tensor_add_zeros_like 0.22% : 0.000002s : 8: predicate.row_tensor_eliminate 1.33% : 0.000014s : 101: predicate.same_eliminate 0.51% : 0.000006s : 52: predicate.set_cell_output_no_recompute 0.27% : 0.000003s : 16: predicate.special_op_eliminate 0.92% : 0.000010s : 50: predicate.specialize_transform 1.72% : 0.000019s : 101: predicate.split_environ_get_set_with_tuple_value 1.46% : 0.000016s : 101: predicate.stack_unstack_eliminate 0.14% : 0.000002s : 8: predicate.switch_call_monad_eliminater 2.94% : 0.000032s : 147: predicate.switch_defer_inline 2.31% : 0.000025s : 147: predicate.switch_layer_defer_inline 5.57% : 0.000060s : 348: predicate.switch_simplify 1.57% : 0.000017s : 101: predicate.tile_eliminate 1.34% : 0.000015s : 101: predicate.transpose_eliminate 1.70% : 0.000018s : 101: predicate.tuple_list_convert_item_index_to_positive 1.81% : 0.000020s : 101: predicate.tuple_list_get_item_depend_reorder 3.10% : 0.000034s : 134: predicate.tuple_list_get_item_eliminator 1.88% : 0.000020s : 101: predicate.tuple_list_set_item_eliminator 1.71% : 0.000019s : 118: predicate.tuple_to_list_eliminator_ 1.79% : 0.000019s : 126: predicate.updatestate_pure_node_eliminater 2.78% : 0.000030s : 172: predicate.updatestate_useless_node_eliminater 1.92% : 0.000021s : 101: predicate.value_based_eliminate 0.11% : 0.000001s : 8: predicate.virtual_view_grad_eliminate 0.13% : 0.000001s : 8: predicate.zero_like_fill_zero ------[func_graph_cloner_run.] 0.364606 79 99.41% : 0.362449s : 42: func_graph_cloner_run.FuncGraphClonerGraph 0.12% : 0.000454s : 7: func_graph_cloner_run.FuncGraphClonerNode 0.47% : 0.001702s : 30: func_graph_cloner_run.FuncGraphSpecializer ------[meta_graph.] 0.000000 0 ------[manager.] 0.000000 0 ------[pynative] 0.000000 0 ------[others.] 2.983597 108 0.00% : 0.000091s : 1: add_recomputation 0.01% : 0.000398s : 1: auto_monad 0.00% : 0.000041s : 1: auto_monad_reorder 0.00% : 0.000004s : 1: backend_pass 0.02% : 0.000603s : 1: bootstrap 0.00% : 0.000042s : 1: cconv 0.00% : 0.000019s : 1: convert_after_rewriter 0.00% : 0.000039s : 1: cse_after_recomputation 0.00% : 0.000017s : 1: environ_conv 1.10% : 0.032846s : 1: event_method 0.00% : 0.000016s : 1: execute 0.00% : 0.000007s : 1: expand_dump_flag 0.00% : 0.000005s : 1: get_jit_bprop_graph 0.00% : 0.000015s : 1: graph_reusing 29.28% : 0.873573s : 1: jit_opt_a 0.01% : 0.000297s : 1: jit_opt_after_cconv 0.00% : 0.000106s : 1: jit_opt_b 0.02% : 0.000558s : 1: loop_unroll 0.03% : 0.001010s : 1: mutable_eliminate 1.50% : 0.044782s : 52: opt.transform.jit_opt_a 0.00% : 0.000133s : 4: opt.transform.jit_opt_after_cconv 0.00% : 0.000067s : 4: opt.transform.jit_opt_b 0.00% : 0.000023s : 1: opt.transform.loop_unroll_optimizer 0.00% : 0.000034s : 1: opt.transform.mutable_eliminate 0.00% : 0.000044s : 1: opt.transform.opt_after_jit_grad 0.04% : 0.001063s : 2: opt.transform.opt_resolve 0.00% : 0.000070s : 4: opt.transform.symbol_engine_opt 0.02% : 0.000570s : 1: opt_after_jit_grad 0.00% : 0.000012s : 1: order_py_execute_after_rewriter 0.00% : 0.000005s : 1: partial_unused_args_eliminate 0.00% : 0.000006s : 1: pre_auto_parallel 0.00% : 0.000060s : 1: py_interpret_to_execute 0.00% : 0.000025s : 1: py_interpret_to_execute_after_opt_a 0.00% : 0.000064s : 1: remove_dup_value 10.93% : 0.326149s : 3: renormalize.infer 0.18% : 0.005235s : 3: renormalize.specialize 0.00% : 0.000011s : 1: rewriter_after_jit_bprop_graph 0.01% : 0.000238s : 1: rewriter_after_opt_a 0.01% : 0.000195s : 1: rewriter_before_opt_a 0.00% : 0.000125s : 1: symbol_engine_optimizer 7.96% : 0.237450s : 1: task_emit 48.85% : 1.457449s : 1: type_inference 0.00% : 0.000103s : 1: validate . [hook] pytest_runtest_teardown:test_permute_zero_bias[KBK] tests/st/mint/test_permute.py::test_permute_zero_bias[KBK],max_mem:4.0M =============================== warnings summary =============================== ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/classifier/transdata/transdata_classifier.py:222: DeprecationWarning: invalid escape sequence \B """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:143: DeprecationWarning: invalid escape sequence \c """ ../../../../../../../../usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170 /usr/local/Ascend/cann-8.5.0/python/site-packages/tbe/dsl/unify_schedule/vector/transdata/common/graph/transdata_graph_info.py:170: DeprecationWarning: invalid escape sequence \c """ ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:549: UserWarning: The value of the smallest subnormal for type is zero. setattr(self, word, getattr(machar, word).flat[0]) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/numpy/core/getlimits.py:89: UserWarning: The value of the smallest subnormal for type is zero. return self._float_to_str(self.smallest_subnormal) ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2.py:57: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad.py:56: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/batchnorm_fold2_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("batchnorm_fold2_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:51: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/correction_mul_grad.py:143: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("correction_mul_grad_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad.py:92: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perlayer_grad_reduce.py:49: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perlayer_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad.py:91: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_learned_scale_quant_perchannel_grad_reduce.py:48: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_learned_scale_quant_perchannel_grad_d_reduce") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel.py:52: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perchannel_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_perchannel_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer.py:54: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/fake_quant_perlayer_grad.py:81: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("fake_quant_per_layer_grad") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perchannel.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perchannel") ../../../../../../anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50 /home/jenkins/anaconda3/envs/ci39/lib/python3.9/site-packages/mindspore/ops/_op_impl/_custom_op/minmax_update_perlayer.py:50: DeprecationWarning: te_fusion.fusion_manager.fusion_manager.register is deprecated,please replace it with tbe.common.register.register_op_compute @fusion_manager.register("minmax_update_perlayer") -- Docs: https://docs.pytest.org/en/stable/warnings.html ================== 2 passed, 25 warnings in 226.21s (0:03:46) ==================